Machine vision systems (also simply termed “vision systems”) use image acquisition devices that include camera sensors to deliver information on a viewed subject. The system then interprets this information according to a variety of algorithms to perform a programmed decision-making and/or identification function. An image of an object containing features of interest to the system is acquired by an on-board image sensor (also termed, simply an “imager” or “sensor”) in the visible, and/or near-visible light range under appropriate illumination, which can be based upon ambient light, and/or light provided by an internal and/or external illuminator.
A common task for vision systems is the reading and decoding of symbology (e.g. one-dimensional and two-dimensional codes—also termed “IDs”) are used in a wide range of applications and industries and can take the form of 1D barcodes, 2D DataMatrix Codes, QR Codes and DotCodes, among others. The image sensor acquires images (typically grayscale or color, and in one, two or three dimensions) of the subject or object, and processes these acquired images using an on-board or interconnected vision system processor. The processor often includes both processing hardware and non-transitory computer-readable program instructions (software) that perform one or more vision system processes to generate a desired output based upon the image's processed information. This image information is typically provided within an array of image pixels each having various colors and/or intensities. In the example of an ID reader (also termed herein, a “camera”), the user or an automated process acquires an image of an object that is believed to contain one or more barcodes, 2D codes or other ID types. The image is processed to identify encoded features, which are then decoded by a decoding process and/or processor to obtain the inherent alphanumeric data represented by the code.
A common form of ID reader used in industrial (and other commercial) applications is the handheld ID reader. This type of reader typically includes a grip that enables the user to carry the reader around a floor space and aim the device at various objects. The grip is provided with one or more trigger buttons that allow the user to direct the acquisition of an image of an object containing an ID after it is aimed at that object. This acquired image is then decoded and the information is transmitted (typically wirelessly) to a receiving unit. The receiving unit transfers the information to another data-handling system, such as an inventory tracking or logistics application running on a server or other computing device (e.g. a PC).
In some vision system applications, particularly handheld ID reading, a projected mark or pattern in the field of view can assist the user in aligning the object's ID code with the reader's camera assembly. This alignment can better ensure a successful read and decoding of the imaged ID. Thus an “aimer” that projects a so-called “aimer pattern” projects one or more bright spots onto the field of view. Several approaches to aimers have been provided in prior designs.
In one approach, an aimer pattern is generated by an optical system parallel to the camera optical axis. The distance between the camera optical axis and the center of the aimer pattern remains the same for all distances, but as the field of view of the camera is increasing at larger distances, the relative offset in the camera image decreases at larger distances. Thus the actual aim point of the system varies at varying distances with larger distances proving more accurate. Alternatively, in another approach, an aimer pattern is generated by an optical system located aside the camera optical axis. This results in an aimer pattern that, at larger or smaller distances, is off-center from the camera optical axis and not predictably located in the field of view. Thus the aim point is only truly aligned at one distance. In yet another approach, an aimer pattern is generated by multiple optical systems symmetrically positioned around the camera, in such way that the center of the pattern is on the camera axis at all distances. This approach requires more space and more projecting lasers (e.g. laser diodes) or LEDs. Also, while the multiple lasers/LEDs can be angled to coincide with variation in the field of view, they do not produce a particular aim point, and may be less intuitive in acquiring a target ID to an inexperienced user. Thus, each of these prior approaches has disadvantages either in the variation of the aim point from the camera optical axis over distance or in complexity and intuitiveness.
A further challenge in designing an ID reader (or other vision system) that is to be used variably at different ranges is that close illumination and distant illumination often require different optical arrangements. An illumination pattern that fully washes a field of view at a short or no distance (i.e. with the reader placed directly against the ID-bearing surface) may not fully illuminate a surface at long distances. Likewise, a long range illuminator is designed to spread out over distance and can appear as discontinuous spots at short distance. In the case of internal illumination, integrated within the housing of a vision system device, space can be limited and the cost of providing a reliable illumination assembly is a concern.